Over the last 100 yr, the dairy industry has incorporated technology to maximize yield and profit. Pressure to maximize efficiency and lower inputs has resulted in novel approaches to managing and milking dairy herds, including implementation of automatic milking systems (AMS) to reduce labor associated with milking. Although AMS have been used for almost 20 yr in Europe, they have only recently become more popular in North America. Automatic milking systems have the potential to increase milk production by up to 12%, decrease labor by as much as 18%, and simultaneously improve dairy cow welfare by allowing cows to choose when to be milked. However, producers using AMS may not fully realize these anticipated benefits for a variety of reasons. For example, producers may not see a reduction in labor because some cows do not milk voluntarily or because they have not fully or efficiently incorporated the AMS into their management routines. Following the introduction of AMS on the market in the 1990s, research has been conducted examining AMS systems versus conventional parlors focusing primarily on cow health, milk yield, and milk quality, as well as on some of the economic and social factors related to AMS adoption. Additionally, because AMS rely on cows milking themselves voluntarily, research has also been conducted on the behavior of cows in AMS facilities, with particular attention paid to cow traffic around AMS, cow use of AMS, and cows' motivation to enter the milking stall. However, the sometimes contradictory findings resulting from different studies on the same aspect of AMS suggest that differences in management and farm-level variables may be more important to AMS efficiency and milk production than features of the milking system itself. Furthermore, some of the recommendations that have been made regarding AMS facility design and management should be scientifically tested to demonstrate their validity, as not all may work as intended. As updated AMS designs, such as the automatic rotary milking parlor, continue to be introduced to the dairy industry, research must continue to be conducted on AMS to understand the causes and consequences of differences between milking systems as well as the impacts of the different facilities and management systems that surround them on dairy cow behavior, health, and welfare.

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Many laying hen producers are transitioning from conventional cages to new housing systems including multi-tier aviaries. Aviary resources, such as litter areas, are intended to encourage hens’ expression of natural behaviors to improve their welfare. Little research has examined the influence of laying hen strain on distribution and behavior inside aviaries, yet differences could influence a strain's suitability for an aviary design. This research examined how laying hens of 4 strains (Hy-Line Brown [HB], Bovans Brown [BB], DeKalb White [DW], and Hy-Line W36) distributed themselves among 3 enclosed aviary tiers and 2 litter areas at peak lay (25 to 28 wk of age) and after gaining access to litter on the floor (26 wk). Observations of hens’ spatial distribution were conducted immediately before and after, and 3 wk after hens gained access to litter. More HB and BB hens were in upper tiers in morning compared to DW and W36 (all P ≤ 0.05). However, DW and W36 hens roosted in upper tiers in larger numbers than HB and BB during evening (all P ≤ 0.05). More DW and W36 hens were on litter compared to BB and HB, particularly when litter was first accessible (all P ≤ 0.05). The number of hens on litter increased over time for all strains (P ≤ 0.06). White hens on litter occupied open areas in higher numbers (P ≤ 0.05), while more brown hens occupied litter under the aviary after acclimation (P ≤ 0.05). In the dark period, W36 and DW hens were present in higher numbers in upper tiers than HB and BB, while HB and BB showed higher tier-to-tier movement than DW and W36 (P ≤ 0.05). In general, more white hens roosted higher at night and explored litter sooner, while more brown hens were near or in nests in the morning and moved at night. Distinct strain differences indicate that attention should be paid to the match between configuration of the aviary design and strain of laying hen.

Lying down and resting are important for optimal cow health, welfare, and production. In comparison with free stall farms with a milking parlor, farms with automated milking systems (AMS) may place less constraint on how long cows can lie down. However, few studies report lying times on AMS farms. The aims of this study were to describe the variation in lying times of dairy cows in AMS farms and to understand how much of the variation in individual lying times is related to cow-level factors, including lameness, the presence of hock and knee lesions, and body condition score (BCS). We visited 36 farms in Canada (Quebec: n = 10; Ontario: n = 10; British Columbia: n = 4; and Alberta: n = 5), and the United States (Michigan: n = 7). Gait scores, presence of hock and knee lesions, and BCS were recorded for 40 Holstein cows from each herd. Parity and days in milk were retrieved from farm records. Lying time was recorded across 4d using accelerometers (n = 1,377). Multivariable analysis was performed. Of scored cows, 15.1% were lame (i.e., obviously limping; 203 of 1,348 cows). Knee lesions were found in 27.1% (340 of 1,256 cows) and hock lesions were found in 30.8% (421 of 1,366 cows) of the animals. Daily lying time varied among cows. Cows spent a median duration of 11.4 h/d lying down (25th-75th percentile = 9.7-12.9 h), with a lying bout frequency of 9.5 bouts/d (25th-75th percentile = 7.5-12 bouts/d) and a median bout duration of 71 min (25th-75th percentile = 58-87 min/bout). Lameness was associated with cows lying down for 0.6 h/d longer in fewer, longer bouts. Increased lying time was also associated with increased parity, later stage of lactation and higher BCS. Older cows (parity ≥ 3) spent about 0.5 h/d more lying down compared with parity 1 cows, and cows with BCS ≥ 3.5 lay down on average 1 h/d longer than cows with BCS ≤ 2.25. Hock lesions were associated with shorter lying times in univariable models, but no associations were found in the multivariable models. We concluded that only a small proportion of the variation between cows in lying time is explained by lameness, leg lesions, and BCS.